Journal ArticleDOI
Identification and Localization of Array Faults With Optimized Placement of Voltage Sensors in a PV System
TLDR
A new, robust, and efficient fault localization method based on the principle of differential voltage measurement between PV modules of adjacent strings is proposed, which is proficient to detect any LL/LG faults independent of its detection challenges and suits both grounded and floating PV systems.Abstract:
The traditional protection devices installed in photovoltaic (PV) arrays generally detect line–line (LL) and line–ground (LG) faults when the fault current magnitude exceeds its threshold value defined by various international standards. However, the magnitude of fault current is greatly reduced, due to low irradiance levels, active maximum power point tracker, location of fault, minimal fault mismatch, and presence of blocking diodes. Consequently, majority of such faults remain obscured even when the irradiance reaches to a higher level and thereby constitute to reliability issues and severe fire risks. Therefore, both timely fault detection and localization become highly obligatory for sustainable power generation and safety. Thus, this article proposes a new, robust, and efficient fault localization method based on the principle of differential voltage measurement between PV modules of adjacent strings. For accomplishing this task, a new optimized voltage sensor arrangement with minimal number of sensors is followed. Moreover, the proposed convention 1) is proficient to detect any LL/LG faults independent of its detection challenges, 2) suits both grounded and floating PV systems, and 3) is compatible for systems with/without blocking diodes. For a realistic validation, testing has been performed on a small-scale grid-connected PV system and the efficacy in detecting various array faults is demonstrated via extensive investigations.read more
Citations
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Journal ArticleDOI
A Diode-Based Fault Detection, Classification, and Localization Method for Photovoltaic Array
TL;DR: In this paper, a diode-based circuit and an algorithm are proposed to detect, classify, and localize faults in small or medium-scale photovoltaic (PV) array with blocking diodes.
Journal ArticleDOI
IoT based fault identification in solar photovoltaic systems using an extreme learning machine technique
Vivek Mohan,S. SenthilKumar +1 more
TL;DR: In this article , the authors proposed an Internet of Things (IoT) sensor-based fault identification in a solar PV system, which uses the IoT cloud to provide real-time monitoring and fault detection in plant environmental and electrical parameters.
Journal ArticleDOI
Asynchronous Decentralized Federated Learning for Collaborative Fault Diagnosis of PV Stations
TL;DR: A novel asynchronous decentralized federated learning (ADFL) framework is proposed, where each PV station not only trains its local model but also participates in collaborative fault diagnosis by exchanging model parameters to improve the generalization without losing accuracy.
Journal ArticleDOI
Asynchronous Decentralized Federated Learning for Collaborative Fault Diagnosis of PV Stations
TL;DR: In this paper , a novel asynchronous decentralized federated learning (ADFL) framework is proposed, where each PV station not only trains its local model but also participates in collaborative fault diagnosis by exchanging model parameters.
References
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Journal ArticleDOI
Line–Line Fault Analysis and Protection Challenges in Solar Photovoltaic Arrays
TL;DR: This paper focuses on line–line faults in PV arrays that may be caused by short-circuit faults or double ground faults, and examines the challenges to OCPD in a PV array brought by unique faults.
Journal ArticleDOI
A Digital Twin Approach for Fault Diagnosis in Distributed Photovoltaic Systems
TL;DR: A digital twin that estimates the measurable characteristic outputs of a PV energy conversion unit (PVECU) in real time is developed that demonstrates higher fault sensitivity than that of existing approaches.
Journal ArticleDOI
Online Fault Detection in PV Systems
TL;DR: In this article, the authors present a fault detection approach for photovoltaic (PV) systems, intended for online implementation, which is based on the comparison between the measured and model prediction results of the ac power production.
Journal ArticleDOI
Fault Detection for Photovoltaic Systems Based on Multi-Resolution Signal Decomposition and Fuzzy Inference Systems
Zhehan Yi,Amir H. Etemadi +1 more
TL;DR: The proposed fault detection scheme is based on a pattern recognition approach that employs a multiresolution signal decomposition technique to extract the necessary features, based on which a fuzzy inference system determines if a fault has occurred.
Journal ArticleDOI
Random forest based intelligent fault diagnosis for PV arrays using array voltage and string currents
TL;DR: The comparison results indicate that the generalization performance of the proposed RF based model is better than the one of the decision tree based model, therefore, the proposed optimal RF based method is an effective and efficient alternative to detect and classify the faults of PV arrays.
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